{"id":"W2359367203","doi":"","title":"Breeding and Utilization of the PTGMS Line P 88 S in Rice","year":2008,"lang":"en","type":"article","venue":"Seed","topic":"Rice Cultivation and Yield Improvement","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Agronomy; Line (geometry); Environmental science; Mathematics; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002389246,0.0003832401,0.0002955364,0.000495732,0.0002479255,0.0002388344,0.0004342926,0.0003348955,0.001857417],"category_scores_gemma":[0.0001723552,0.0002890151,0.0004440137,0.0003979315,0.0003043434,0.0001649932,0.0003454061,0.0007687752,0.0009592381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002781959,"about_ca_system_score_gemma":0.0003315127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009475522,"about_ca_topic_score_gemma":0.001451331,"domain_scores_codex":[0.9998499,0.00003550237,0.00001997115,0.00004557834,0.00002741468,0.00002158661],"domain_scores_gemma":[0.9998672,0.00002720569,0.00002684339,0.00002821486,0.00001169222,0.00003886213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000812254,0.00004268969,0.000325493,0.00001489221,0.000003829807,0.00008815488,0.00002566364,0.00007542465,0.996663,0.0001356608,0.00004577185,0.002498136],"study_design_scores_gemma":[0.0001731151,0.001068245,0.01942454,0.00001928091,0.0001296571,0.001612399,0.0001311893,0.003798811,0.9619745,0.0002222467,0.01142032,0.00002567819],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9875178,0.0001720459,0.009705711,0.0001294106,0.00002391553,0.00007233009,0.0005203926,0.0002262337,0.001632253],"genre_scores_gemma":[0.9757057,0.0002879449,0.01478468,0.00008458349,0.00001540878,0.0000845102,0.002300687,0.0001801731,0.006556462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001857417,"threshold_uncertainty_score":0.006213725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06636652988672818,"score_gpt":0.2389260067733583,"score_spread":0.1725594768866301,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}